Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review” [Clin Imaging 118 (2025) 110369]

Elinor Laws; Joanne Palmer; Joseph Alderman; Ojasvi Sharma; Victoria Ngai; Thomas Salisbury; Gulmeena Hussain; Sumiya Ahmed; Gagandeep Sachdeva; Sonam Vadera; Bilal Mateen; Rubeta Matin; Stephanie Kuku; Melanie Calvert; Jacqui Gath; Darren Treanor; Melissa McCradden; Maxine Mackintosh; Judy Gichoya; Hari Trivedi; Alastair K. Denniston; Xiaoxuan Liu

doi:10.1016/j.clinimag.2025.110541

Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review” [Clin Imaging 118 (2025) 110369]

Elinor Laws
, Joanne Palmer
, Joseph Alderman
, Ojasvi Sharma
, Victoria Ngai
, Thomas Salisbury
, Gulmeena Hussain
, Sumiya Ahmed
, Gagandeep Sachdeva
, Sonam Vadera
, Bilal Mateen
, Rubeta Matin
, Stephanie Kuku
, Melanie Calvert
, Jacqui Gath
, Darren Treanor
, Melissa McCradden
, Maxine Mackintosh
, Judy Gichoya
, Hari Trivedi

Alastair K. Denniston, Xiaoxuan Liu^*

^*Corresponding author for this work

Research output: Contribution to journal › Comment/debate

Abstract

The authors provide a correction rectify an error in the reporting of one dataset titled “Mammogram Mastery: A Robust Dataset for Breast Cancer Detection and Medical Education” within the original publication. The erratum includes minor edits to the numerical figures within the main body of text (for the categories race or ethnicity, derived from screening programme, consent, and sex or gender there is one additional dataset within the count). The edited counts are reflected within associated numerical figures within Table 1, Fig. 3, and Appendix 5.

The authors would like to apologize for any inconvenience caused.

[Tables presented]

Original language	English
Article number	110541
Number of pages	4
Journal	Clinical Imaging
Volume	125
Early online date	8 Jul 2025
DOIs	https://doi.org/10.1016/j.clinimag.2025.110541
Publication status	Published - Sept 2025

Bibliographical note

Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review” [Clin Imaging 118 (2025) 110369].

Publisher Copyright:
© 2024 The Authors

Keywords

Artificial intelligence
Mammography

ASJC Scopus subject areas

Radiology Nuclear Medicine and imaging

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.clinimag.2025.110541Licence: Creative Commons: Attribution-NonCommercial-NoDerivs (CC BY-NC-ND)

LawsE2025CorrigendumFinal published version, 860 KBLicence: Creative Commons: Attribution-NonCommercial-NoDerivs (CC BY-NC-ND)

1 Review article

Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review
Laws, E., Palmer, J., Alderman, J., Sharma, O., Ngai, V., Salisbury, T., Hussain, G., Ahmed, S., Sachdeva, G., Vadera, S., Mateen, B., Matin, R., Kuku, S., Calvert, M., Gath, J., Treanor, D., McCradden, M., Mackintosh, M., Gichoya, J. & Trivedi, H. & 2 others, Denniston, A. K. & Liu, X., Feb 2025, In: Clinical Imaging. 118, 49 p., 110369.
Research output: Contribution to journal › Review article › peer-review

Open Access
File

Cite this

Laws, E., Palmer, J., Alderman, J., Sharma, O., Ngai, V., Salisbury, T., Hussain, G., Ahmed, S., Sachdeva, G., Vadera, S., Mateen, B., Matin, R., Kuku, S., Calvert, M., Gath, J., Treanor, D., McCradden, M., Mackintosh, M., Gichoya, J., ... Liu, X. (2025). Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review” [Clin Imaging 118 (2025) 110369]. Clinical Imaging, 125, Article 110541. https://doi.org/10.1016/j.clinimag.2025.110541

@article{09ab52bb3bd0464c9959418a05417230,

title = "Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review” [Clin Imaging 118 (2025) 110369]",

abstract = "The authors provide a correction rectify an error in the reporting of one dataset titled “Mammogram Mastery: A Robust Dataset for Breast Cancer Detection and Medical Education” within the original publication. The erratum includes minor edits to the numerical figures within the main body of text (for the categories race or ethnicity, derived from screening programme, consent, and sex or gender there is one additional dataset within the count). The edited counts are reflected within associated numerical figures within Table 1, Fig. 3, and Appendix 5.The authors would like to apologize for any inconvenience caused. [Tables presented]",

keywords = "Artificial intelligence, Mammography",

author = "Elinor Laws and Joanne Palmer and Joseph Alderman and Ojasvi Sharma and Victoria Ngai and Thomas Salisbury and Gulmeena Hussain and Sumiya Ahmed and Gagandeep Sachdeva and Sonam Vadera and Bilal Mateen and Rubeta Matin and Stephanie Kuku and Melanie Calvert and Jacqui Gath and Darren Treanor and Melissa McCradden and Maxine Mackintosh and Judy Gichoya and Hari Trivedi and Denniston, \{Alastair K.\} and Xiaoxuan Liu",

note = "Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review” [Clin Imaging 118 (2025) 110369]. Publisher Copyright: {\textcopyright} 2024 The Authors",

year = "2025",

month = sep,

doi = "10.1016/j.clinimag.2025.110541",

language = "English",

volume = "125",

journal = "Clinical Imaging",

issn = "0899-7071",

}

Laws, E, Palmer, J, Alderman, J, Sharma, O, Ngai, V, Salisbury, T, Hussain, G, Ahmed, S, Sachdeva, G, Vadera, S, Mateen, B, Matin, R, Kuku, S, Calvert, M, Gath, J, Treanor, D, McCradden, M, Mackintosh, M, Gichoya, J, Trivedi, H, Denniston, AK & Liu, X 2025, 'Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review” [Clin Imaging 118 (2025) 110369]', Clinical Imaging, vol. 125, 110541. https://doi.org/10.1016/j.clinimag.2025.110541

TY - JOUR

T1 - Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies

T2 - a systematic review” [Clin Imaging 118 (2025) 110369]

AU - Laws, Elinor

AU - Palmer, Joanne

AU - Alderman, Joseph

AU - Sharma, Ojasvi

AU - Ngai, Victoria

AU - Salisbury, Thomas

AU - Hussain, Gulmeena

AU - Ahmed, Sumiya

AU - Sachdeva, Gagandeep

AU - Vadera, Sonam

AU - Mateen, Bilal

AU - Matin, Rubeta

AU - Kuku, Stephanie

AU - Calvert, Melanie

AU - Gath, Jacqui

AU - Treanor, Darren

AU - McCradden, Melissa

AU - Mackintosh, Maxine

AU - Gichoya, Judy

AU - Trivedi, Hari

AU - Denniston, Alastair K.

AU - Liu, Xiaoxuan

N1 - Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review” [Clin Imaging 118 (2025) 110369]. Publisher Copyright: © 2024 The Authors

PY - 2025/9

Y1 - 2025/9

N2 - The authors provide a correction rectify an error in the reporting of one dataset titled “Mammogram Mastery: A Robust Dataset for Breast Cancer Detection and Medical Education” within the original publication. The erratum includes minor edits to the numerical figures within the main body of text (for the categories race or ethnicity, derived from screening programme, consent, and sex or gender there is one additional dataset within the count). The edited counts are reflected within associated numerical figures within Table 1, Fig. 3, and Appendix 5.The authors would like to apologize for any inconvenience caused. [Tables presented]

AB - The authors provide a correction rectify an error in the reporting of one dataset titled “Mammogram Mastery: A Robust Dataset for Breast Cancer Detection and Medical Education” within the original publication. The erratum includes minor edits to the numerical figures within the main body of text (for the categories race or ethnicity, derived from screening programme, consent, and sex or gender there is one additional dataset within the count). The edited counts are reflected within associated numerical figures within Table 1, Fig. 3, and Appendix 5.The authors would like to apologize for any inconvenience caused. [Tables presented]

KW - Artificial intelligence

KW - Mammography

UR - https://www.scopus.com/pages/publications/85210547689

U2 - 10.1016/j.clinimag.2025.110541

DO - 10.1016/j.clinimag.2025.110541

M3 - Comment/debate

SN - 0899-7071

VL - 125

JO - Clinical Imaging

JF - Clinical Imaging

M1 - 110541

ER -

Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review” [Clin Imaging 118 (2025) 110369]

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Research output

Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review

Cite this